The image of the wall of the borehole comprises a two-dimensional array of numbers, each number being the magnitude of a relevant borehole parameter at a point on the borehole wall. In the image, the co-ordinates of the point are given by the circumferential direction and the depth along the borehole. A tilted planar event intersecting a cylindrical borehole wall is shown on the image as a sinusoidal line.
The image is used for sedimentological and structural geological interpretation of the formation around the borehole. In this image relevant events have to be distinguished from the intersections shown in the image, this is normally done manually, however several automatic procedures have also been developed in the industry. These are generally based on variants of dip-meter algorithms, that determine cross-correlations of the button signals of the dip-meter in order to establish the orientation of formation layers intersecting the borehole wall. Dipmeter algorithms, however, are most suited to determine continuous or slowly varying bedding dips, but they are not capable of detecting intersecting planar events or single thin events that have an orientation that significantly deviates from the bedding orientation. For this reason, dipmeter algorithms are not useful to detect fractures in borehole images and the development of automatic procedures for fracture detection is an active area of research.
Such an image can be obtained by employing an acoustic tool, such as the Ultrasonic Borehole Imager (UBI) tool available from Schlumberger or the Circumferential Borehole imaging Logging (CBIL) tool available from Baker. These tools obtain an image from the borehole wall by emitting a focused beam of high-frequency acoustic energy towards the borehole wall, followed by a series of measurements on the signal that is reflected back from the borehole wall. Such an image can also be obtained by employing a microresistivity tool such as the Fullbore Micro Imager or the Formation Micro Scanner available from Schlumberger. The microresistivity tool comprises a number of pads with individual electrodes, which pads are during normal operation in contact with the borehole wall. The image can also be obtained by employing any other suitable tool.
U.S. Pat. No. 5,960,371 discloses a method of detecting significant planar events intersecting a borehole from an image of the borehole wall, which image comprises a two-dimensional array of numbers, each number being the magnitude of a relevant borehole parameter at a point defined by the circumferential direction φ and the depth z, which method comprises the steps of:    (a) determining for each point i of the image the slope ηi of the sinusoids by computing the edge gradient direction;    (b) selecting a parameter relation (zi=d−R tan Φ cos (φi−α)) that represents the intersection of a planar event with the borehole wall, wherein the intersection is characterized by three parameters (Φ, α, d);    (c) creating a discretized three-dimensional parameter space consisting of numbers as a function of the three parameters (Φ, α, d), wherein each number is a measure of the support for a sinusoid passing through (φi, zi) with slope ηi characterized by the parameters that pertain to that number;    (d) selecting in the parameter space a set of the largest numbers, wherein the parameters that pertain to each of these largest numbers represent the intersections of the significant planar events with the borehole wall; and    (e) presenting the intersections pertaining to the set of the largest numbers as a list of data representing significant planar events.
The intersection that pertains to the values for each parameter that pertain to the significant planar events can be presented to obtain a treated image.
Steps (c) and (d) of the known method are implemented via a so-called Hough Transformation. Improving the Hough Transformation by using the edge gradient direction is known from the article ‘Generalizing the Hough transform to detect arbitrary shapes’, D. H. Ballard, Pattern Recognition, Vol. 13, No. 2, pages 111–122, 1981.
In the known method information obtained from the edge gradient direction is used to further constrain the number of sets of parameters for which the support has to be evaluated. A disadvantage of the known method is that the edge detector is only capable of detecting the most prominent local orientation, which is insufficient in case of combined fractures and bedding or in case of intersecting fractures.